Design of hierarchical fuzzy systems based on subtractive clustering and adaptive neuro-fuzzy inference systems
基于减法聚类和自适应神经模糊推理系统的递阶模糊系统的设计

An easy and effective method to design hierarchical fuzzy systems is presented.The degree of importance of each input variable was obtained using sensitivity analysis method based on a single stage fuzzy model.After ranking of importance of each input variable,input variables of every subsystem of the hierarchical fuzzy system can be determined.Every subsystem was trained from the first stage to the last stage using subtractive clustering and ANFIS (adaptive neuro-fuzzy inference systems).A method to reduce the hierarchical fuzzy system was proposed.The design method was proved to be feasible.